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cs.AI updates on arXiv.org

Detecting Safety Violations Across Many Agent Traces C-ReD: A Comprehensive Chinese Benchmark for AI-Generated Text Detection Derived from Real-World Prompts ClawGUI: A Unified Framework for Training, Evaluating, and Deploying GUI Agents General365: Benchmarking General Reasoning in Large Language Models Across Diverse and Challenging Tasks Discourse Diversity in Multi-Turn Empathic Dialogue Evaluating Cooperation in LLM Social Groups through Elected Leadership SWE-AGILE: A Software Agent Framework for Efficiently Managing Dynamic Reasoning Context Agentic Driving Coach: Robustness and Determinism of Agentic AI-Powered Human-in-the-Loop Cyber-Physical Systems Legal2LogicICL: Improving Generalization in Transforming Legal Cases to Logical Formulas via Diverse Few-Shot Learning Playing Along: Learning a Double-Agent Defender for Belief Steering via Theory of Mind RPA-Check: A Multi-Stage Automated Framework for Evaluating Dynamic LLM-based Role-Playing Agents A Triadic Suffix Tokenization Scheme for Numerical Reasoning Synthius-Mem: Brain-Inspired Hallucination-Resistant Persona Memory Achieving 94.4% Memory Accuracy and 99.6% Adversarial Robustness on LoCoMo Time is Not a Label: Continuous Phase Rotation for Temporal Knowledge Graphs and Agentic Memory NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment Policy Split: Incentivizing Dual-Mode Exploration in LLM Reinforcement with Dual-Mode Entropy Regularization METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models Quantization Dominates Rank Reduction for KV-Cache Compression Anthropogenic Regional Adaptation in Multimodal Vision-Language Model Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search Trajectories Do LLMs Know Tool Irrelevance? Demystifying Structural Alignment Bias in Tool Invocations The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning The Past Is Not Past: Memory-Enhanced Dynamic Reward Shaping RECIPER: A Dual-View Retrieval Pipeline for Procedure-Oriented Materials Question Answering Exploring Knowledge Conflicts for Faithful LLM Reasoning: Benchmark and Method CocoaBench: Evaluating Unified Digital Agents in the Wild MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis Use of AI Tools: Guidelines to Maintain Academic Integrity in Computing Colleges Efficient Training for Cross-lingual Speech Language Models Guardrails Beat Guidance: A Large-Scale Study of Rules, Skills, and Persistent Configuration for Coding Agents Towards Proactive Information Probing: Customer Service Chatbots Harvesting Value from Conversation Shared Emotion Geometry Across Small Language Models: A Cross-Architecture Study of Representation, Behavior, and Methodological Confounds A Systematic Analysis of the Impact of Persona Steering on LLM Capabilities Uncertainty-Aware Web-Conditioned Scientific Fact-Checking Min-$k$ Sampling: Decoupling Truncation from Temperature Scaling via Relative Logit Dynamics When Valid Signals Fail: Regime Boundaries Between LLM Features and RL Trading Policies When Verification Fails: How Compositionally Infeasible Claims Escape Rejection Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoning A molecular clock for writing systems reveals the quantitative impact of imperial power on cultural evolution Mem$^2$Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience Distillation Audio Flamingo Next: Next-Generation Open Audio-Language Models for Speech, Sound, and Music ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval AOP-Smart: A RAG-Enhanced Large Language Model Framework for Adverse Outcome Pathway Analysis Speaking to No One: Ontological Dissonance and the Double Bind of Conversational AI Advancing Polish Language Modeling through Tokenizer Optimization in the Bielik v3 7B and 11B Series TInR: Exploring Tool-Internalized Reasoning in Large Language Models Do BERT Embeddings Encode Narrative Dimensions? 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Instructing LLMs to Negotiate using Reinforcement Learning with Verifiable Rewards COMPOSITE-Stem GIANTS: Generative Insight Anticipation from Scientific Literature Pioneer Agent: Continual Improvement of Small Language Models in Production SafeAdapt: Provably Safe Policy Updates in Deep Reinforcement Learning Many-Tier Instruction Hierarchy in LLM Agents Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories PhysInOne: Visual Physics Learning and Reasoning in One Suite Neural Distribution Prior for LiDAR Out-of-Distribution Detection Interactive ASR: Towards Human-Like Interaction and Semantic Coherence Evaluation for Agentic Speech Recognition PDE-regularized Dynamics-informed Diffusion with Uncertainty-aware Filtering for Long-Horizon Dynamics Leave My Images Alone: Preventing Multi-Modal Large Language Models from Analyzing Images via Visual Prompt Injection CONSCIENTIA: Can LLM Agents Learn to Strategize? Emergent Deception and Trust in a Multi-Agent NYC Simulation Regime-Conditional Retrieval: Theory and a Transferable Router for Two-Hop QA
AI and Machine Learning Driven Indoor Localization and Navigation with Mobile Embedded Systems
Sudeep Pasricha · 2024-08-09 · via cs.AI updates on arXiv.org

Indoor navigation is a foundational technology to assist the tracking and localization of humans, autonomous vehicles, drones, and robots in indoor spaces. Due to the lack of penetration of GPS signals in buildings, subterranean locales, and dense urban environments, indoor navigation solutions typically make use of ubiquitous wireless signals (e.g., WiFi) and sensors in mobile embedded systems to perform tracking and localization. This article provides an overview of the many challenges facing state-of-the-art indoor navigation solutions, and then describes how AI algorithms deployed on mobile embedded systems can overcome these challenges.

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